Determining loads using various sensor locations

ABSTRACT

A system and method for pressure based load measurement are provided. The system and method measure at least one pressure differential on an airfoil and determine at least one aerodynamic load associated with the at least one pressure differential. The determined at least one load is used to modify characteristics of the airfoil to increase efficiency and/or avoid damage. The determined at least one aerodynamic load may be further utilized to balance and/or optimize loads at the airfoil, estimate a load distribution along the airfoil used to derive other metrics about the airfoil, and/or used in a distributed control system to increase efficiency and/or reduce damage to, e.g., one or more wind turbines.

TECHNICAL FIELD

Aspects relate to determining load on a device using various sensorlocations.

BACKGROUND

Measurement of load in mechanical and electronic devices is often usedto optimize performance. Excessive loads may strain the system andresult in damage or lower efficiency. In the aerodynamics field, forexample, blades or wings may be susceptible to excess loads due to thedirection and magnitude of air flow. Similarly, in hydrodynamics, loadssustained from water flow may also affect efficiency and increase thepotential for damage. To measure loads, various types of sensors may beused including pressure gauges, strain gauges, force sensors (e.g.,transducers) and the like. In some instances, the placement of thevarious sensors may affect the accuracy of the load measurements.

SUMMARY

This summary is provided to introduce a selection of concepts in asimplified form that are further described below in the DetailedDescription. The Summary is not intended to identify key features oressential features of the claimed subject matter, nor is it intended tobe used to limit the scope of the claimed subject matter.

Aspects described herein relate to determining or estimating load on adevice based on various placements of sensors on the device. In oneexample, determining the aerodynamic load on a turbine blade or airplanewing may involve identifying barometric (i.e., ambient air) pressure,ambient air temperature, rotor speed, blade pitch angle, radial locationof sensors, and blade twist angle. Using these factors, an aerodynamicload may be calculated using a predetermined number of sensors includedin the blade. For example, two pressure sensors may be used to determinea pressure differential. Based on the pressure differential of the twosensors and one or more of the factors noted above, the aerodynamic loadon the blade may be determined.

According to some aspects of the disclosure, determining or estimatingan aerodynamic load on an aerodynamic load-bearing member might onlyrequire placement of two pressure sensors on the aerodynamicload-bearing member. Other data inputs used to calculate the aerodynamicload may be determined from the pressure sensors or other sensors thatare not mounted on or otherwise included in the blade. For example,ambient air temperature may be calculated using a temperature gaugemounted on the rotor, nacelle, or tower.

According to other aspects of the disclosure, determining or estimatingan aerodynamic load may be used to balance loads on the blades of a windturbine. For example, two pressure sensing orifices may be provided ateach blade of a wind turbine to determine a pressure differential. Usingthe pressure differential and other factors listed above, a load may beestimated at each blade. The loads at each blade may be compared todetermine if loads are balanced among the blades and/or if loads at eachblade are within an optimal range.

According to other aspects of the disclosure, determining or estimatingan aerodynamic load on an aerodynamic load bearing member may be used todetermine or estimate a load distribution along the member. Determininga load distribution along the aerodynamic load bearing member may beused to determine other metrics associated with the member including,e.g., displacement of the load bearing member, velocity of the loadbearing member, acceleration of the load bearing member, and a momentacting on the load bearing member.

According to other aspects of the disclosure, distributed controlsystems may be used within a wind turbine or among multiple windturbines. These distributed control systems may modify one or morecharacteristics of each wind turbine in response to estimating loadsassociated with one or more wind turbines. In one embodiment, multiplecontrollers perform desired modifications such that each controller mayact as a substitute or failsafe in the event another fails. In anotherembodiment, a controller may modify characteristics in response to acontroller at a related wind turbine estimating a load at the relatedwind turbine.

BRIEF DESCRIPTION OF THE DRAWINGS

The foregoing summary of the invention, as well as the followingdetailed description of illustrative embodiments, is better understoodwhen read in conjunction with the accompanying drawings, which areincluded by way of example, and not by way of limitation with regard tothe claimed invention.

FIG. 1 illustrates a perspective view of a wind turbine according to oneembodiment of the disclosure.

FIG. 2 illustrates a cross-section of an airfoil comprising a pressurebased load measurement system according to one embodiment of thedisclosure.

FIG. 3A illustrates a graph depicting a normal force coefficient versusa pressure differential coefficient according to one embodiment of thedisclosure.

FIG. 3B illustrates a graph depicting a tangential force coefficientversus a pressure differential coefficient according to one embodimentof the disclosure.

FIG. 4 illustrates exemplary forces acting on an aerodynamic loadbearing member according to one embodiment of the disclosure.

FIG. 5 illustrates a flowchart of a method for determining arelationship between a force coefficient and a pressure differentialcoefficient as well as a relationship between a rotor speed and/or bladepitch angle and wind velocity according to one embodiment of thedisclosure.

FIG. 6 illustrates a flowchart of a method for controlling one or moreairfoil characteristics in response to determining loads acting on theairfoil according to one embodiment of the disclosure.

FIG. 7 illustrates modifying one or more characteristics of a windturbine blade according to one embodiment of the disclosure.

FIG. 8 illustrates a flowchart for a method of balancing blades and/oroptimizing loads on a wind turbine according to one embodiment of thedisclosure.

FIG. 9 illustrates an control system determining a load distribution onan airfoil according to one embodiment of the disclosure.

FIG. 10A illustrates an example load distribution on a wind turbineblade according to one embodiment of the disclosure.

FIG. 10B illustrates another example load distribution on a wind turbineblade according to one embodiment of the disclosure.

FIG. 11 illustrates an example wind turbine comprising multiplecontrollers according to one embodiment of the disclosure.

FIG. 12 illustrates an example system of multiple wind turbines withmultiple controllers according to one embodiment of the disclosure.

DETAILED DESCRIPTION

In the following description of various illustrative embodiments,reference is made to the accompanying drawings, which form a parthereof, and in which is shown, by way of illustration, variousembodiments in which the invention may be practiced. It is to beunderstood that other embodiments may be utilized and structural andfunctional modifications may be made without departing from the scope ofthe present invention.

FIG. 1 illustrates a wind turbine 2 on a foundation 4 with a tower 6supporting a nacelle 8. One or more blades 10 are attached to a hub 12via a bolt flange 14. The hub 12 is connected to a drive train (notshown) within the nacelle 8. In one arrangement, blades 10 may be fixedlength rotor blades having root portion 16 and tip portion 18. Inanother arrangement, the blades 10 may be variable length blades havinga root portion 16 and a tip portion 18. Variable length blades may beconfigured to extend and retract given certain conditions. Various modesfor controlling a variable length blade may be used to optimize orotherwise increase the effectiveness of such blades and/or a turbinesuch as wind turbine 2 to which the blades are attached. Any desirabledrive system, such as a screw drive, a piston/cylinder, or apulley/winch arrangement may be used to move the tip portion 18 withrespect to the root portion 16. Such drive systems are described in U.S.Pat. No. 6,902,370, titled “Telescoping Wind Turbine,” and filed Jun. 4,2002, which is hereby incorporated by reference. The wind turbine 2further includes a yaw drive and a yaw motor, and may include a pitchcontrol system, not shown. Alternatively or additionally, blades 10 mayinclude a mix of variable length and fixed length rotor blades.

According to yet other aspects, blades 10 may include one or moredeployable air deflectors configured to modify airflow by extending froma surface of blades 10. In other embodiments, additional features (notshown) and/or methods may be used to modify airflow along a blade. Forexample, blade pitch may be modified, one or more plasma actuators maybe actuated, a wind turbine may utilize active suction/blowing, one ormore flaps disposed on a blade may be activated, etc., in order tomodify the airflow. Modification of the airflow may result in theincrease of lift and/or decrease in load. A controller may thus modifythe power output, efficiency, load and the like using the deployable airdeflectors. Examples of deployable air deflectors are described in U.S.patent application Ser. No. 12/122,584, titled “Wind Turbine with GustCompensation Air Deflector,” and filed May 16, 2008, which is herebyincorporated by reference.

FIG. 2 illustrates one example cross section of an airfoil, such as froman airplane wing, wind turbine blade, etc. as used in conjunction withthe present disclosure. The airfoil includes a leading edge 22, atrailing edge 24, a top surface 26, and a bottom surface 28. A chordline, c, can be defined as a line between the leading edge 22 and thetrailing edge 24 of the airfoil 20. The airfoil 20 shown in FIG. 2 ismerely one illustrative cross-sectional design and it is recognized thatinfinite cross-sectional variations can be used as part of the presentinvention. The airfoil 20 may be made of any suitable construction andmaterials, such as fiberglass and/or carbon fiber.

With further reference to FIG. 2, the blade 20 includes orifices at twopressure sensing locations, P1 and P2. P1 is located on the bottomsurface 28 of the blade 20 and P2 is located on the top surface 26 ofthe blade 20. A pressure transducer, 30, is provided to measure pressuredifferential between the two pressure sensing locations. Locations 30 a,30 b indicate opposing sides of the pressure transducer diaphragm todetermine the pressure differential between each point P1 and P2. In analternate arrangement, multiple pressure transducers may be used. Thelocation of P1 and P2 shown in FIG. 2 is merely illustrative of oneexample location of each orifice. The location of P1 and P2 may begenerally dependent on the blade 20 or wing cross-sectional geometry. Inone example, the location of the pressure sensors and ports maycorrespond to 0.125 c and 0.150 c on the pressure and suction surfaces,respectively, where c represents the chord length. This range may, insome examples, be preferable to reduce the error to within a specifiedthreshold (e.g., 7%). In some embodiments, P1 and P2 may be disposed,e.g., between 5% and 70% of the length of chord c, and, in someembodiments, disposed, e.g., between 10% and 60% of the length of chordc.

Using the pressure differential between P₁ and P₂, a controller maydetermine various loads of a blade including a lifting load, a normalforce load, a tangent force load, an in-plane (power producing) load,and a rotor normal load. More specifically, the aerodynamic forces andmoments generated along the span of a blade are proportional to adifference in pressure between two points on an airfoil surface. Using adetermined local dynamic pressure and the measured pressure differential(i.e., the difference in pressures between P₁ and P₂), the loads actingupon a blade can be readily determined. Generally, the local dynamicpressure (or estimated value thereof) may be determined using thefollowing equation:

q _(est)≡½ρ_(∞) v _(est) ²  (1)

where ρ_(∞) corresponds to the ambient air density and v_(est)corresponds to the estimated local air speed at the pressure sensors.For a wind turbine, an estimate of the wind air speed can be obtainedusing the rotor speed and wind speed, as defined in equation 2:

v _(est)≡√{square root over (ω_(rotor) ² r _(sensor) ² v _(wind,est)²)}  (2)

That is, an estimated value of local air speed in the vicinity of thepressure sensors (v_(est)) may be calculated using the known rotor speed(ω_(rotor)) the radial position of the pressure sensors (r_(sensor)),and the wind speed (v_(wind,est)). In some instances, the wind speedmight not be directly measureable (e.g., sensors might not be used orincluded in the blade or turbine to measure the wind speed). In suchinstances, the wind speed may be determined empirically using the windturbine as an anemomenter. The following set of equations estimate windspeed based upon the rotor speed depending on the pitch angle of theblade (β):

$\begin{matrix}{v_{{wind},{est}} \approx \left\{ \begin{matrix}{{\kappa_{\omega \; 1}\omega_{rotor}} + \kappa_{\omega \; 0}} & {{{for}\mspace{14mu} \beta} = {\beta_{\min \mspace{11mu}}\left( {{Region}\mspace{14mu} {II}} \right)}} \\{{\kappa_{p\; 2}\beta^{2}} + {\kappa_{p\; 1}\beta} + \kappa_{p\; 0}} & {{{for}\mspace{14mu} \beta} > {\beta_{\min}\mspace{14mu} \left( {{Region}\mspace{14mu} {III}} \right)}}\end{matrix} \right.} & (3)\end{matrix}$

where κ_(ω#) and κ_(p#) represent empirically determined coefficientsand β represents the blade pitch having a minimum of β_(min). Thedifferent regions may have different load profiles and thus requiredifferent algorithms or formulas for determining the estimated loadgiven the various data inputs. As one particular example in whichsimulations were performed for a 750 kW ZOND™ turbine with a 48 m rotorcomprised of three EUROS™ blades, the following Region II and Region IIIcoefficients were determined:

Region II Region III κ_(ω1) = 2.913 m/rad κ_(p2) = 68.739 m/(s · rad²)κ_(ω0) = −0.094 m/s κ_(p1) = 14.307 m/(s · rad) κ_(p0) = 10.331 m/s

Once the local dynamic pressure has been calculated, it is used tonondimensionalize the measured pressure differential, resulting in apressure differential coefficient (C_(ΔP)) as detailed in equation 4:

$\begin{matrix}{C_{\Delta \; p} \equiv \frac{\Delta \; p}{q_{est}}} & (4)\end{matrix}$

This pressure differential coefficient, along with empiricallydetermined constants, can be used to estimate each load associated withthe blade. Specifically, in one embodiment, in order to calculate any ofthe above-noted loads (e.g., lifting load, normal force load, tangentforce load, in-plane load) based on the measured pressure differential,a coefficient for each force corresponding to each load is calculatedusing the determined pressure differential coefficient. Equations 5, 6,and 7 are example formulas for calculating the lift force coefficient(C_(l,est)), normal force coefficient (C_(n,est)), and tangent forcecoefficient (C_(t,est)), respectively. In some arrangements, thesecoefficients may represent estimated coefficients or values rather thanactual.

C _(l,est)≡κ_(l0) C _(Δp)+κ_(l0)  (5)

C _(n,est)≡κ_(n1) C _(Δp)+_(n0)  (6)

C _(t,est)≡κ_(t2) C _(Δp) ²+κ_(t1) C _(Δp)+κ_(t0)  (7)

In equations 5, 6, and 7, κ_(l#), κ_(n#) and κ_(t#) each representempirical coefficients that may depend upon local blade section geometryand pressure orifice installation locations. As shown by equations 5, 6,and 7, the pressure differential coefficient has a linear relationshipwith each of the lift force coefficient and the normal forcecoefficient, and has a quadratic relationship with the tangent forcecoefficient. To determine each of the empirical coefficients, the linearor quadratic relationship may be fitted to empirical or calculated datacollected for the type of blade (e.g., blade section geometry) and/orpressure sensor installation locations.

FIG. 3A illustrates an example linear fit between the pressuredifferential coefficient (C_(Δp)) and the normal force coefficient(C_(n)) based on empirical data for a particular type of blade andsensor installation location. For example, simulations and/or tests maybe performed on a blade of the particular type and having the pressuresensors located at the sensor installation locations. The results of thetests and/or simulation may then be analyzed to identify a linearrelationship between C_(Δp) and C_(n). In some arrangements, best-fitalgorithms (e.g., least squares) may be used to compute the relationshipbetween the pressure differential coefficient and each of the othercoefficients.

Similarly, FIG. 3B illustrates an example quadratic relationship betweenthe pressure differential coefficient (C_(Δp)) and the tangential forcecoefficient (C_(t)). Again, data collected through empirical studies andanalyses may be used to derive the quadratic relationship for aparticular type of blade and/or pressure sensor installation location.

FIG. 4 is a diagram illustrating example forces acting upon a rotorblade 401 along with an example wind vector 403. The illustrated forcesinclude the resultant force (R), lift force (f_(l)), drag force (f_(d)),normal force (f_(n)), tangent force (f_(t)), rotor-normal force (F_(N)),and rotor-tangent force (F_(T)). For example, the rotor-normal forceF_(N) is perpendicular to the rotor plane 407 while the normal forcef_(n) is normal to the chord line 405 of the rotor blade 401. The forcesnormal to the rotor plane 407 may be used to determine root bendingmoments, which contributes to stress on the blade. Accordingly, controlsmay be implemented to minimize the root bending moments or to optimizepower output. In one example, optimizing power output may includebalancing the root bending moment while maximizing in-planepower-producing loads. Modification of bending moments, normal loads,power-producing loads, and other forces may be controlled in a varietyof ways including changing blade pitch or yaw, deploying air deflectors,extending/retracting expandable and retractable blades, and the like, asis described in further detail below.

Using the estimated lift force, normal force, and tangent forcecoefficients (as determined by, e.g., equations 5, 6, and 7respectively), and the estimated local dynamic pressure (as determinedby, e.g., equation 1), the lifting load (

), normal force load (η), and tangent force load (τ) may be estimatedbased on the following equations:

≡q _(est) C _(l,est)  (8)

η≡q _(est) C _(n,est)  (9)

τ≡q _(est) C _(t,est)  (10)

Equations 8, 9, and 10 estimate aerodynamic loads in the localchord-fixed reference frame. In general, these loads can be translatedinto other reference frames if the appropriate transformation angles areknown. For example, the load normal to the rotor plane may be calculatedusing the determined normal and tangent force loads of the localchord-fixed reference frame based on the following equation:

L _(n)≡η cos(θ_(sensor)+β)+τ sin(θ_(sensor)+β)  (11)

where θ_(sensor) corresponds to the blade twist angle at the sensorlocation and β corresponds to the blade pitch angle (as discussed).Generally, the top and bottom sensors will be located in correspondingradial positions on a top surface and a bottom surface of the blade.Accordingly, the blade twist angle will be the same. To calculate thenormal load in the blade-fixed reference frame, β is set to zero.

Similarly, the tangential loads relative to various reference frames maybe calculated based on the determined normal and tangent force loads(relative to the local chord-fixed reference frame). For example, thefollowing tangential load equation may be applied:

L _(T)≡η sin(θ_(sensor)+β)−τ cos(θ_(sensor)+β)  (12)

Again, the tangential load in the blade-fixed reference frame may becalculated by setting the blade pitch angle β to zero.

FIG. 5 illustrates a flowchart of an example method for empiricallydetermining the relationship between each load coefficient and thepressure differential coefficient, as well as empirically determiningthe relationship between the rotor speed and/or the blade pitch angleand the wind speed. These empirically determined relationships may laterbe used when determining loads on a wind turbine blade using a singlepressure differential as discussed more fully below.

In step 500, a computing system may collect, receive or otherwisedetermine load information generated based on empirical tests andanalyses (e.g., simulations, field tests, data for turbines in service,etc.). The computing system may comprise a controller for modifying orotherwise setting characteristics of a wind turbine, an airfoil, devicesin or on an airfoil, sets of wind turbines and the like and/orcombinations thereof. The computing system may correspond to acontroller for an air deflector device in one or more examples.Alternatively or additionally, the computing system may correspond to acontroller for an entire blade. In yet other examples, the computingsystem may be configured to control all or a subset of devices within awind turbine. In still another example, the computing system may beconfigured to control multiple wind turbines. Using the collected loaddata, the coefficients of lift force (C_(l)), normal force (C_(n)),tangent force (C_(t)), and pressure differential (C_(Δp)) may becalculated or otherwise determined in step 505. For example, thepressure differential coefficient may be calculated from the receivedload information based on the equation:

$\begin{matrix}{C_{\Delta \; p} = \frac{p - p_{\infty}}{q_{\infty}}} & (13)\end{matrix}$

where ρ is the local pressure measured on the blade surface, ρ_(∞) isthe barometric (i.e., ambient air) pressure, and q_(∞) is the dynamicpressure. The dynamic pressure may be calculated using the followingequation:

q _(∞)=½·ρ_(∞) ·v _(∞) ²  (14)

where ρ_(∞) is the ambient air density and v_(∞) is ambient air speed.The ambient air density may be determined according to the perfect gaslaw using the ambient air temperature (T_(∞)) and the gas constant fordry air (R_(air), which has a value of 287 J/(kg K)), according to thefollowing equation:

$\begin{matrix}{\rho_{\infty} = \frac{p_{\infty}}{R_{air}T_{\infty}}} & (15)\end{matrix}$

A coefficient for each force may be calculated from the received loadinformation and the determined dynamic pressure based on the equation:

$\begin{matrix}{C_{F} = \frac{F}{A \cdot q_{\infty}}} & (16)\end{matrix}$

where F is the force associated with coefficient being calculated (e.g.,lift, normal, tangential, etc.), and A is the nominal area the force isacting upon (defined as π times the nominal diameter squared, alldivided by four). For example, with respect to the lift, the nominalarea the lift force is acting on may be, e.g., the blade planform area.

Upon determining each of these coefficients, relationships may bederived or otherwise determined between the pressure differentialcoefficient and each of the lift coefficient, the normal forcecoefficient, and the tangent force coefficient in step 510. As discussedabove and illustrated in FIG. 3A and FIG. 3B, the relationship may be,e.g., a linear relationship or a quadratic relationship and may bedetermined using best fit algorithms such as least squares and the like.In one example, the lift and normal force coefficients may have a linearrelationship with the pressure differential coefficient while thetangent force coefficient may have a quadratic relationship with thepressure differential coefficient. In step 515, the constants (e.g.,κ_(l#), κ_(n#), and κ_(t#)) resulting from the determined relationshipsmay be extracted and stored. For example, the constants may be stored ina storage device in an airfoil, in a turbine, or in a central controllerconfigured to control multiple turbines.

In step 520, the system may further collect (e.g., receive) or otherwisedetermine measured wind velocity data (v_(wind)), detected rotor speedinformation (ω_(rotor)) and blade pitch angle (β). This information maybe measured, in some examples, during empirical tests and/orsimulations. Using the collected data, the system may, in step 525,determine (e.g., calculate) relationships between the wind velocity dataand one or more of the rotor speed and the blade pitch angle. Forexample, a first relationship may be defined for a minimum blade pitchangle (β_(min)) of the rotor blade while a second relationship may bedetermined for blade pitch angles above the minimum blade pitch angle.Examples of the various relationships are shown in equation set 3. Theserelationships (between wind velocity and rotor speed and/or blade pitchangle), as with the pressure differential coefficient relationships, maybe determined using empirical data and best fit algorithms such as aleast squares. Once the relationships have been determined, theconstants for the wind velocity relationships may then be extracted andstored in step 530 for subsequent use.

By identifying the various relationships between load coefficients andpressure differential coefficients, and between rotor speed and bladepitch angles and wind speed, a turbine control system may appropriatelymodify blade and turbine characteristics in response to compensate foror otherwise address various loads and load conditions. In one example,a turbine control system may modify blade or turbine characteristicssuch as deployment/retraction of air deflectors on a blade,extension/retraction of a tip portion of a blade, modifying pitch and/oryaw angles, and the like. In some instances, the turbine control systemmay modify blade characteristics to optimize the lift-to-drag ratio, asdescribed in further detail below.

FIG. 6 illustrates an example method for controlling one or more bladeand turbine characteristics based on load determinations, such as thosemade according to aspects described herein (e.g., using a singlepressure differential). One or more control systems may be used tocontrol the blade and/or turbine characteristics. The control system(s)may be located in the blade, in the turbine, or in a control room remotefrom the turbine. The control system may also be configured to control asingle device (e.g., a single air deflector, single rotor blade, singleturbine) or multiple devices (e.g., multiple air deflectors, multiplerotor blades, multiple turbines). In step 600, the control system mayreceive or determine pressure sensor data from a pair of pressureorifices on a blade while the turbine is in operation. In one example,the data may be provided wirelessly or through wired connections and/orusing one or more public or private networks. In step 605, the controlsystem may determine the pressure differential (Δp) between the pressuresensor readings from the two pressure sensing orifices (e.g., P₁ and P₂in FIG. 2), a rotor speed (ω_(rotor)), barometric (i.e., ambient air)pressure (ρ_(∞)), ambient air temperature (T_(∞)), and a blade pitchangle (e.g., positive toward feather, β). In various arrangements, thecontrol system may determine at least two of a rotor speed (ω_(rotor)),barometric (i.e., ambient air) pressure (ρ_(∞)), ambient air temperature(T_(∞)), and a blade pitch angle (e.g., positive toward feather, β). Inother examples, the control system might only determine one of theaforementioned characteristics.

In step 610, the control system may determine the local air speed(v_(est)). The local air speed, as shown in equation 2, may bedetermined based on one or more of the estimated wind speed(v_(wind, est)), the rotor speed, and the radial location of the sensors(r_(sensor)), and/or combinations thereof. In some arrangements, thelocation of the sensor may be predefined and pre-stored (e.g.,determined at the time of installation into the blade). The estimatedwind speed, in turn, may be calculated based on the rotor speed and/orthe blade pitch angle as shown in equation set 3. In a particularexample, the control system may determine whether the blade pitch angleis above a predefined minimum blade pitch angle (β_(min)), as notedabove. If so, a first determination algorithm or formula may be used togenerate the estimated wind speed. If, however, the blade pitch angle isequal to the minimum, the control system may apply a second algorithm orformula to generate the estimated wind speed.

Using the local air speed, the control system may determine the localdynamic pressure in step 615 according to, for example, equation 1 shownabove. The ambient air density (ρ_(∞)) may be calculated based on theperfect gas law using the barometric (i.e., ambient air) pressure(ρ_(∞)), the gas constant for dry air (R_(air)), and the ambient airtemperature (T_(υ)) according to equation 15. Using the pressuredifferential received in step 600 and the local dynamic pressuredetermined in step 615, the pressure differential coefficient may thenbe calculated by the control system in step 620. For example, anestimated pressure differential coefficient may be determined usingequation 4. In steps 625-635, the determined pressure differentialcoefficient may then be used to determine the desired loads.Specifically, at step 625 the control system may retrieve the determinedconstants for each of the various load coefficient to pressuredifferential coefficient relationships determined, extracted and storedin step 515 of the flowchart in FIG. 5. Using the retrieved constantsand the type of coefficient-to-coefficient relationship, in step 630 thecontrol system may then estimate each of the lift, normal, and tangentload coefficients based on, e.g., equations 5, 6, and 7, respectively.The loads may then be derived based on each of the coefficients and thelocal dynamic pressure in step 635. For example, the lift load (

) may be calculated by multiplying the local dynamic pressure with thelift load coefficient as presented equation 8. Similarly, the normalforce load (η) and the tangent force load (τ) may be determined bymultiplying the local dynamic pressure with the normal force loadcoefficient and the tangent force load, respectively, as presented inequations 9 and 10. The rotor-normal load (L_(N)) and rotor-tangent load(L_(T)) may also be calculated using, for example, equations 11 and 12,respectively.

Once the loads have been determined, the control system may compare oneor more of the loads to specified load thresholds to determine if theloads exceed, meet, or fall below the thresholds in step 640. Dependingon the results of the comparison, the control system may modify one ormore blade or turbine characteristics in step 645. For example, if therotor-normal load exceeds a specified threshold, the control system maydeploy one or more air deflectors on the blade to reduce stress andstrain on the blade. In another example, if the rotor-tangent load fallsbelow a specified threshold, the control system may modify a blade pitchto increase the rotor-tangent load (e.g., to increase power production).In other examples, controls may be based on a combination of loads suchas both the rotor-normal load and the rotor-tangent load. In particular,the control system may modify blade and turbine characteristics tooptimize the ratio between the rotor-tangent load and the rotor-normalload.

According to some arrangements, the estimated load profile and variouscoefficients used to determine a load based on a single pressuredifferential reading (e.g., normal, tangential, and lift forcecoefficients described above), may change depending on the blade orturbine characteristics. For example, different coefficients and/orlinear or quadratic correlations may be defined for different sets ofblade or turbine characteristics. In a particular example, a firstcorrelation/relationship may be defined and used to determine load if afirst set of one or more air deflectors are deployed while a secondcorrelation/relationship may be defined and used if a second set of oneor more air deflectors are deployed (or if no air deflectors aredeployed). Similarly, different pitches or yaws (or combinationsthereof) may also affect the correlation/relationship defined and usedto determine the load. Accordingly, a control system may store a varietyof different load determination equations/relationships andautomatically select the appropriate relationship depending on thecurrently existing blade and/or turbine characteristics when the load isto be determined.

Selecting the equation/relationship to be used in load determination maybe performed based on minimizing an estimated amount of error. Forexample, if an equation or relationship is not defined for a current setof parameters of the turbine (e.g., the particular deflector(s)activated, the pitch or yaw angle, and/or combinations thereof), acontrol system may select a relationship for another set of turbineparameters that would result in the smallest estimated amount of errorfor the current set of turbine parameters. Error in using a relationshipdefined for a first set of turbine parameters to calculate load for asecond set of turbine parameters may be estimated using a variety ofmethods, including empirical testing.

Using load determination techniques such as those described herein, aturbine control system may further perform blade balancing and/oroptimization. In one example, one or more blades of the turbine may beadjusted to balance detected loads among all of the blades. Accordingly,if one blade is experiencing higher loads than other blades, one or morecharacteristics of the one blade may be adjusted to bring the load downto the level detected by the other blades. For example, a pitch or yawof the higher-load blade may be adjusted and/or air deflectors on thehigher-load blade may be deployed. In other examples, if the blade is avariable length blade, a tip portion may be extended or retracted tomodify effective loads. Individual or groups of blades (e.g., less thanall blades, predefined sub-groups of blades, etc.) may be controlledseparately from the other blades.

Determined loads may also be used to optimize various characteristics ofthe turbine's operation. For example, the lift-to-drag ratio of one ormore blades may be optimized to maximize power generation. Thus, in aparticular example, a blade's pitch may be modified to increase thelift-to-drag ratio, thereby increasing power generation. Again, as withblade balancing, each individual blade may be controlled separately fromthe other blades. Additionally or alternatively, sub-groups of bladesmay be defined and controlled together separately from other blades orsub-groups of blades. Turbine control may also include evaluation ofslices of the blade path. Accordingly, if a slice of the blade path isdetermined to be experiencing a higher load than other portions of theblade path, a control system may modify, e.g., the yaw of the turbine tocompensate and equalize the loads.

Balancing and optimization of turbine operation may be performed on thefly or during a turbine down state. Accordingly, a turbine may becontrolled continuously, at predefined times, or upon detection of acondition (e.g., lift-to-drag is below a specified threshold) duringoperation to insure that power generation is maximized and/or otherobjectives are met. The ability to balance and modify bladecharacteristics after installation eliminates the need to remove bladesor disassemble other parts of the turbine in order to performancebalancing and other adjustments.

FIG. 7 illustrates one embodiment wherein a turbine control systemperforms blade balancing and/or optimization. Specifically, FIG. 7illustrates wind turbine 700 comprising three blades, 702 a, 702 b, and702 c. Blades 702 a, 702 b, and 702 c comprise pressure sensors 704 a,704 b, and 704 c, respectively. Each pressure sensor 704 may comprisetwo orifices (P₁ and P₂) and transducer 30 as illustrated in FIG. 2. Apressure differential can thus be measured at each blade 702 by eachpressure sensor 704. Each blade 702 may further comprise variouscontrols, systems, and the like which may vary different characteristicsof the blade 702 in order to bring loads acting on each blade to adesired level. For example, each blade may comprise an air deflector706, which may be deployed or refracted, or tip portion 708, which maybe extended or retracted. Further, each blade 702 may be configured suchthat the pitch and/or yaw of the blade may be adjusted in response todetected loads.

In the embodiment depicted in FIG. 7, blade 702 c is adjusted inresponse to turbine control system 714 sensing that the loads actingblade 702 c are out of balance with those acting on each of the othertwo blades, 702 a and 702 b, and/or are not within a predetermined rangeof acceptable loads. Specifically, turbine control system 714 receivespressure differential readings from each of pressure sensors 704 a, 704b, and 704 c. Using, e.g., any of the load determination techniques asdescribed above, turbine control system 714 determines that blade 702 cneeds adjustment in order to bring loads into acceptable load rangesand/or balance the loads with those associated with blades 702 a and 702b. Accordingly, turbine control system 714 may adjust one or morecharacteristic of blade 702 c. For example, turbine control system 714may deploy air deflector 706 c, as illustrated by arrow 710.Alternatively or additionally, turbine control system 714 may extend orretract tip portion 708 c as shown illustrated by arrow 712, and/orturbine control system 714 may alter the pitch or yaw of blade 702 c asillustrated by arrows 714.

By receiving a pressure differential reading from each blade 702 of awind turbine 700, turbine control system 714 may thus determine loadsassociated with each blade and make adjustments to the characteristicsof each blade if necessary to bring the effective loads within apredetermined acceptable range and/or balance the loads among eachblade. In the embodiment illustrated in FIG. 7, only blade 702 c isshown as receiving adjustment, however, as will be well understood giventhe benefit of this disclosure, more than one blade and/or more than onecharacteristic of each blade may be adjusted in order to balance and/oroptimize loads among each blade. For example, in another embodiment, inresponse to receiving pressure differential readings from each blade,turbine control system 714 may deploy the air deflector 706 c of blade702 c, adjust the pitch of blade 702 a, and extend or retract tipportion 708 b of blade 702 b. Any other combination of adjustingcharacteristics among each blade to achieve a desired load distributionmay be readily employed without departing from the scope of thisdisclosure.

FIG. 8 illustrates a flowchart of an example method for optimizingand/or balancing blades of a wind turbine. At step 800, pressure sensordata is determined by a control system. Pressure sensor data may bedetermined (e.g., received, calculated, measured, etc.) from a pluralityof pressure sensors on a plurality of blades. For example, returning toFIG. 7, pressure sensor data may be received from pressure sensors 704a, 704 b, and 704 c on blades 702 a, 702 b, and 702 c, respectively. Atstep 805, pressure differentials may be determined from the receivedpressure sensor data. For example, each pressure sensor 704 may includea pressure orifice on the bottom surface of a blade and a pressuresensor orifice on a top surface of a blade (such as P₁ and P₂ in FIG.2). The system, at step 805 may thus determine a difference in pressurebetween these two orifices which, as presented above, may beproportional to loads the blade is experiencing.

At step 810, these loads may be determined using, e.g., any of theaforementioned methods. In some embodiments, other characteristics inaddition to pressure differential may be used to determine loads. Forexample, the system may use one or more of the rotor speed of the windturbine, barometric (i.e., ambient air) pressure, ambient airtemperature, a sensor radial location, a twist angle of the wind turbineblade, and/or a pitch angle of the wind turbine blade in determiningloads acting on the blade. At step 815, the system may determine whetherthe loads are out of balance. For example, in one embodiment the loadsexperienced by a first of the wind turbine blades may be compared to theloads experienced by other wind turbine blades. If the loads experiencedby the first blade are out of balance with the loads experienced byother blades, the method may proceed to step 820. If, however, the loadsare not out of balance, the system may proceed to step 825. At step 820,characteristics of the blade are modified in order to bring the loadacting a first blade back in balance. For example, if the blade isequipped with a deployable air deflector, the method may deploy the airdeflector. Additionally or alternatively, the method may change thepitch angle of the blade or the yaw angle of the turbine and/or blade tobalance the loads. Or the method may extend or retract a tip portion ofthe blade. Any modification at this step may be made in “real time;”i.e., while the wind turbine is rotating or during a turbine down state.Accordingly, the method may bring blades into balance while the windturbine is operating to avoid, e.g., downtime and lost productivity.

The system may also determine whether determined loads are within anacceptable range at step 825. For example, the system may determineloads acting on a blade are too high, and accordingly modify, e.g., anyof the abovementioned characteristics in response at step 830 in orderto avoid damage to the blade. Alternatively or additionally, the systemmay determine that, e.g., a lift-to-drag ratio is too low and modify anyof the abovementioned characteristics at step 830 in order to increasepower generation. Again, any modification at step 830 may be made in“real time;” to avoid, e.g., downtime and lost productivity, or during aturbine down state.

In some embodiments of the disclosure, using any of load estimationtechniques as described above, a load profile may be determined orestimated along the length of an airfoil or a blade. For example, theload estimation techniques as described above may be used to determine,e.g., a rotor-normal and/or rotor-tangent loads at multiple locationsalong an airfoil or blade. Using the estimated loads at multiplelocations, a load distribution may be determined. This load distributionmay be used to when deriving additional metrics about the airfoil orblade. For example, a load distribution may be used to determine a rootbending moment acting on an airfoil or blade. If the root bending momentis too high, a control system may alter one or more characteristics toreduce the moment and thus avoid damage to the rotor and/or the blades.Conversely, if the root bending moment is too low, a control system mayalter one or more characteristics to increase the moment in order to,e.g., increase power generation. Alternatively, a load distribution maybe used to derive the displacement (e.g., the flex or twist) of anairfoil or blade. Or, a load distribution may be used to determinevelocities and accelerations associated with an airfoil or blade.Accordingly, using, e.g., any of the aforementioned techniques, acontrol system for a wind turbine may derive many useful metrics used inthe control of the wind turbine by merely estimating loads associatedwith at least one blade of the turbine.

FIG. 9 illustrates an example of control system 906 determining a loaddistribution on blade 902 c of a wind turbine. In FIG. 9, wind turbine900 comprises a hub 908 and three blades, 902 a, 902 b, and 902 c. Blade902 c is equipped with a plurality of pressure sensors 904. In theembodiment depicted, only blade 902 c is shown having pressure sensors904 for simplicity, however, in some embodiments more than one blade maycomprise one or more pressure sensors. Pressure sensors 904 maycomprise, e.g., two pressure sensing orifices (P₁ and P₂) and atransducer 30 as depicted in FIG. 2. Accordingly, control system 906 mayreceive data corresponding to multiple pressure differentials along thelength of blade 902 c. Specifically, each pressure sensor 904 _(n) maydetermine a pressure at P_(1,n) (i.e., a bottom surface of blade 902 c)and a pressure at P_(2,n) (i.e., a top surface of blade 902 c) anddetermine a pressure differential between the two locations. Thus, foreach radial location along blade 902 c where each pressure sensor 904,is located, control system 906 may receive data regarding a differencein pressure on the top of blade 902 c and the bottom of blade 902 c.Control system 906 may then use the received pressure differential ateach location to estimate a load distribution along blade 902 c using,e.g., any of the load estimation techniques described herein.

For example, as depicted in FIG. 9, control system 906 is depicted asestimating the rotor-normal load (L_(N)) and tangential load (L_(T)) ateach radial location. In other embodiments, control system 906 mayestimate, e.g., the lifting load (

), the normal load (η), the tangential load (τ), and/or any otherdesired loads. Once any desired loads are determined, control system 906determines a load distribution along blade 902 c and may further use theload distribution to determine other metrics associated with windturbine 900. For example, control system 906 may use the loaddistribution to determine a displacement of blade 902 c, including anamount of flex or twist of blade 902 c. Alternatively, control system906 may determine an acceleration or velocity of blade 902 c and/or windturbine 900 accordingly to the load distribution. By measuring pressuredifferentials along the radial length of blade 902 c, a control system906 may thus estimate a load distribution and derive other relevantmetrics accordingly.

The magnitude of each estimated load L_(N,n) and L_(T,n) as depicted inFIG. 9 is for illustrative purposes only. In other embodiments, theforces estimated at each location along blade 902 c may have, e.g., alinear or quadratic relationship. For example, in one embodiment, therotor-normal load may be linearly proportional to the radial distance ofpressure sensor 904 _(n) from the hub 908. Thus, the rotor-normal loadmay increase proportionally to the radial length from hub 908, andaccordingly the load distribution would appear more uniform that thosedepicted in FIG. 9. Alternatively, control system 906 may, e.g., striveto achieve a linear and/or quadratic relationship among the loads alongthe length of blade 902 c. Thus, upon estimating the loads along thelength of blade 902 c, controller 906 may determine that the loads arenot proportional to the corresponding pressure sensor 904 _(n) radialdistance from hub 908 (i.e., the loads are out-of-balance). Accordingly,controller 906 may adjust one or more characteristics of blade 902 c asdiscussed herein in order to bring the loads back into balance.

FIGS. 10A and 10B illustrate two example embodiments of a balanced loaddistribution along a wind turbine blade. In FIG. 10A, wind turbine 1000comprises three blades 1002 a, 1002 b, and 1002 c. For simplicity,blades 1002 a and 1002 b have not been fully illustrated. Blade 1002 cmay be equipped with pressure sensors along its length (not shown) suchas the pressure sensor described above with respect to FIG. 2 and/orpressure sensors 904 described above with respect to FIG. 9. Eachpressure sensor along the length of blade 1002 c measures a pressuredifferential at its location, wherein the pressure differentialcorresponds to a difference in pressure between a top surface of blade1002 c and a bottom surface of blade 1002 c. Using, e.g., any of theload distribution techniques discussed herein, a control system (notshown) may estimate the loads along the length of blade 1002 c. Forexample, as illustrated, a control system may calculate the rotor-normalload (L_(N)) at each location. Alternatively or additionally, a controlsystem may estimate any load discussed herein. In this embodiment, therotor-normal load distribution is linear. Thus, the controller maydetermine the blade is in balance. Additionally or alternatively, thecontrol system may use the linear distribution to calculate othermetrics corresponding to blade 1002 c, such as, e.g., displacement,acceleration, velocity, and/or moment. Using these metrics thecontroller may more efficiently control the wind turbine by, e.g.,modifying characteristics of the wind turbine blade 1002 c in order tobring the loads into a desired range and/or balance the loads with loadsacting on other blades (e.g., 1002 a and/or 1002 b).

FIG. 10B represents an alternative load distribution which may beestimated by the control system and/or which the control system mayadjust characteristics of the blade in order to achieve. In theembodiment illustrated in FIG. 10B, the load distribution is no longerlinear, but rather may have, e.g., a quadratic or other nonlinearrelationship. The load distribution may vary depending on, e.g.,configuration of the wind turbine, environmental conditions, and/orother factors. Regardless of the actual characteristics of the loaddistribution, a control system may use the load distribution indetermining other metrics of the blade or wind turbine and/or adjustblade characteristics in order to achieve a desired distribution.

The determined load value at discrete points along a rotor blade, asillustrated in FIGS. 10A and 10B, may be used to calculate adistribution. For example, a linear or quadratic fit may be determinedto generate an equation corresponding to the distribution. Using thisdistribution, load values at other points (e.g., points where a pressuresensor or other sensing device is not located) may be calculated orotherwise determined.

In other embodiments of the present disclosure, one or more windturbines may comprise a distributive control system. In one embodimentof the distributed control system, a wind turbine may comprise multiplecommunicatively coupled controllers. For example, a wind turbine mayhave a function-specific controller for each modifiable characteristicof a wind turbine blade. A wind turbine may thus comprise one controllerwhich controls an extendable tip portion of a wind turbine blade, onecontroller which controls a pitch of the wind turbine blade, onecontroller which controls a yaw of the wind turbine and/or the windturbine blade, one controller which controls an air deflector on thewind turbine blade, and/or one or more controllers which controls one ormore additional characteristics of the wind turbine blade. Additionally,the wind turbine may comprise a central controller capable ofcontrolling one or more of the above-mentioned characteristics. In suchembodiments, each function-specific controller may act as a failsafe orsubstitute for the central controller, and/or the central controller mayact as a failsafe or substitute for each function-specific controller.For example, with respect to an air deflector, a central controller aswell as an air-deflector controller may be configured to control theoperation of the air deflector. If, for example, the central controllerfails, the air-deflector controller may control the air deflector if andwhen a wind turbine blade needs adjusted. Alternatively, if theair-deflector controller fails, the central controller may control theair deflector if and when the wind turbine blade needs adjusted.Accordingly, a wind turbine may avoid damage and/or shutdown if acontroller fails because another controller may perform a substituteoperation.

FIG. 11 illustrates one embodiment of a distributive control systemusing multiple controllers. In FIG. 11, wind turbine 1100 comprisesthree blades, 1104 a, 1104 b, and 1104 c. Each blade 1104 and/or windturbine 1100 may be configured such that a number of characteristics maybe altered in response to, e.g., detection of excessive and/orout-of-balance loads. For example, each blade 1104 may have a tipportion which is configured to extend or detract. Further, each blade1104 may have an air deflector which can be deployed or refracted. Stillfurther, each blade 1104 may be configured such that the pitch or yaw ofeach blade may be altered in order to modify the loads acting on theblade 1104. Wind turbine 1100 may comprise a central controller 1102which is configured to modify one or more characteristic of wind turbine1100 and/or blades 1104. For example, central controller 1102 may beconfigured to modify one or more of pitch angle and yaw angle for eachblade 1104, and/or may be configured to extend or retract one or more ofan air deflector and/or a tip portion of each blade 1104.

In addition to central controller 1102, wind turbine 1100 may furthercomprise function-specific controllers configured to modify variouscharacteristics of wind turbine 1100 and/or blades 1104. Specifically,each blade may comprise a pitch and/or yaw controller 1106, airdeflector controller 1108, and/or variable length controller 1110.Accordingly, each characteristic of blades 1104 may be modified usingthe function-specific controllers. Further, each function-specificcontroller may be redundant with, e.g., central controller 1102. Forexample, central controller 1102 as well as variable length controller1110 may be configured to modify the length of one or more blades 1104in order to modify loads and/or bring loads in balance. Accordingly,when modifying the length of blades 1104, either central controller 1102or variable-length controller 1110 may be used. If one of thecontrollers should fail, the other controller may still perform thedesired modification in response to excessive and/or out-of-balanceloads. Accordingly, each controller provides a failsafe, becausecharacteristics of wind turbine 1100 may be modified in order to, e.g.,avoid damage even if one or more controllers fails.

In another embodiment of a distributed control system, multiplecontrollers among multiple wind turbines may be communicatively coupledin order to provide efficient operation and/or avoid damage due toexcessive loads. For example, in one embodiment, multiple wind turbinesmay be arranged near each other. Each wind turbine may comprise one ormore controllers configured to modify one or more characteristics ofeach wind turbine. For example, each turbine may comprise one or morecontrollers which extend or retract a tip portion of its blades, modifya pitch angle of its blades, modify a yaw angle of the wind turbineand/or its blades, and/or deploy or retract air deflectors on itsblades. The controllers may communicate with each other and adjustcharacteristics accordingly. By way of example, a controller at a firstwind turbine may detect excessive loads at the turbine using, e.g., anyof the aforementioned load estimation techniques. The first wind turbinemay then adjust any number of characteristics in order to prevent, e.g.,damage to the turbine caused by the excessive loads. Additionally, oneor more controllers at the wind turbine may then communicate with one ormore controllers located at other wind turbines. Accordingly, thecontrollers at the other wind turbine may adjust one or morecharacteristics in response to the first wind turbine's loaddetermination. Thus, damage can be reduced in the other turbines and/orthe other turbines may be operated more efficiently.

FIG. 12 illustrates one embodiment wherein multiple controllers arecommunicatively coupled in order to provide a distributed control systemamong multiple wind turbines. Specifically, wind farm 1200 comprisesmultiple wind turbines 1202 communicatively coupled to each otherthrough control system 1208. Each wind turbine 1202 may communicate withone another using any well-known method including wired or wirelesscommunication. Characteristics of each wind turbine 1202 (e.g., pitch,yaw, length of blades, air deflectors deployed or not) are configured tobe modified in response to, e.g., a determination that loads acting oneach turbine 1202 are excessive and/or out of balance. Methods forestimating loads and/or modifying one or more characteristics may beperformed by, e.g., any of the methods provided herein. Each windturbine 1202 may further be arranged into groups. For example, windturbines 1202 a-1202 f may be arranged into group 1204, and windturbines 1202 g-1202 k may be arranged into group 1206. Each windturbine 1202 may further comprise one or more controllers (not pictured)to control the one or more modifiable characteristics of each windturbine 1202.

A controller at each wind turbine 1202 and/or control system 1208 mayestimate excessive loads employing, e.g., any of the loadestimation/determination techniques described herein. For example, windturbine 1202 g may be subject to a sudden wind gust 1208. Depending on,e.g., the current configuration of wind turbine 1202 g, wind gust 1208may cause excessive loads on wind turbine 1202 g. In response, one ormore controllers at wind turbine 1202 g may modify one or morecharacteristics. For example, a controller may modify the yaw of windturbine 1202 g such that the wind turbine faces directly into the windgust. Additionally or alternatively, a controller may adjust the pitchor yaw of one or more blades, may deploy or retract an air deflector onone or more blades, and/or may extend or retract a tip portion of one ormore blades. Further, wind turbine 1202 g may be communicatively coupledto one or more of controllers of the other wind turbines 1202 a-1202 kvia, e.g., control system 1208. Accordingly, other wind turbines 1202may use load estimation or determination and/or characteristicmodification data from wind turbine 1202 g in order to modifycharacteristics in preparation for, e.g., a wind gust 1208. For example,if 1202 g is subjected to wind gust 1208 which causes excessive loads,and wind turbine 1202 g thus modifies a yaw angle of wind turbine 1202 gin response, one or more of the other wind turbines 1202 may adjusttheir respective yaw angle in preparation of wind gust 1208.Accordingly, wind turbines such as, e.g., 1202 h and 1202 e, which maybe located far downwind from wind turbine 1202 g, may compensate forwind gust 1208 before such a gust ever reaches each turbine. Thus, inthis embodiment, controllers distributed throughout multiple windturbines may be used to increase efficiency and/or reduce failures ofwind turbines 1202 by using feedback from one or more turbines.

Wind farm 1200 may further comprise groupings of wind turbines such as,e.g., groups 1204 and 1206. Accordingly, characteristics of each turbine1202 may only be modified when, e.g., other turbines in the same groupare modified. For example, it may be determined that wind turbines 1202a-1202 f generally experience the same environmental conditions as eachother due to, e.g., their location on a ridge, while wind turbines 1202g-1202 k usually experience the same environmental conditions as eachother but that are typically distinct from those experienced by windturbines 1202 a-1202 f. Thus, wind turbines 1202 a-1202 f may be groupedinto group 1204, and wind turbines 1202 g-1202 k may be grouped intogroup 1206. Accordingly, when wind turbine 1202 g experiences, e.g.,wind gust 1208, it may adjust any number of characteristics as explainedabove, and the other turbines grouped with wind turbine 1202 g in group1206 (i.e., wind turbines 1202 h-1202 k) may similarly adjustcharacteristics to compensate for expected increased loads, while windturbines in group 1204 (i.e., wind turbines 1202 a-1202 f) may notmodify any characteristics in response. Accordingly, in some aspects ofthe present disclosure, a distributed control system can be used toincrease efficiency and decrease failure of groupings of wind turbines1202 which are typically exposed to similar environmental conditions.

The methods and features recited herein may further be implementedthrough any number of computer readable media that are able to storecomputer readable instructions. Examples of computer readable mediumsthat may be used include RAM, ROM, EEPROM, flash memory or other memorytechnology, CD-ROM, DVD or other optical disk storage, magneticcassettes, magnetic tape, magnetic storage and the like.

While illustrative systems and methods as described herein embodyingvarious aspects of the present invention are shown, it will beunderstood by those skilled in the art, that the invention is notlimited to these embodiments. Modifications may be made by those skilledin the art, particularly in light of the foregoing teachings. Forexample, each of the elements of the aforementioned embodiments may beutilized alone or in combination or subcombination with elements of theother embodiments. It will also be appreciated and understood thatmodifications may be made without departing from the true spirit andscope of the present invention. The description is thus to be regardedas illustrative instead of restrictive on the present invention.

We claim:
 1. A method for determining an aerodynamic force associatedwith an airfoil, the method comprising: determining, by an airfoilcontrol device, a pressure differential between a first pressurelocation and a second pressure location on an airfoil; determining, bythe airfoil control device, at least two of: a rotation speed of theairfoil, an ambient air pressure, an ambient air temperature, and apitch angle of the airfoil; and determining, by the airfoil controldevice, an aerodynamic force associated with the airfoil based on thepressure differential, and the at least two of: the rotation speed ofthe airfoil, the ambient air pressure, the ambient air temperature, andthe pitch angle of the airfoil.
 2. The method of claim 1, wherein thedetermining the aerodynamic force associated with the airfoil comprisesestimating a local dynamic pressure at the airfoil based on the at leasttwo of: the rotation speed of the airfoil, the ambient air pressure, theambient air temperature, and the pitch angle of the airfoil.
 3. Themethod of claim 2, wherein the estimating the local dynamic pressure atthe airfoil comprises estimating a local air speed at the airfoil. 4.The method of claim 3, wherein the estimating the local air speed of theairfoil comprises estimating a wind speed at the airfoil.
 5. The methodof claim 4, wherein the estimating the wind speed at the airfoilcomprises determining whether the pitch angle of the airfoil is greaterthan a minimum pitch angle.
 6. The method of claim 5, wherein, when thepitch angle of the airfoil is not greater than a minimum pitch angle,the estimating the wind speed at the airfoil is performed based on therotation speed of the rotor.
 7. The method of claim 5, wherein, inresponse to determining the pitch angle of the airfoil is greater than aminimum pitch angle, the estimating the wind speed at the airfoil isbased on the pitch angle of the airfoil.
 8. The method of claim 1further comprising: modifying at least one characteristic of the airfoilin response to determining the aerodynamic force associated with theairfoil.
 9. The method of claim 8, wherein the modifying the at leastone characteristic of the airfoil comprises at least one of: changingthe pitch angle of the airfoil; changing a yaw angle of the airfoil;deploying at least one air deflector; retracting the at least one airdeflector; extending a tip portion of the airfoil; and retracting thetip portion of the airfoil.
 10. A wind turbine comprising: a hub; acontroller; and a plurality of wind turbine blades connected to andarranged about the hub, wherein at least one wind turbine blade of theplurality of wind turbine blades comprises: a first pressure sensingorifice arranged on a bottom surface of the at least one wind turbineblade; and a second pressure sensing orifice arranged on a top surfaceof the at least one wind turbine blade, wherein the first pressuresensing orifice and the second pressure sensing orifice are configuredto enable the controller to determine an aerodynamic load generated bythe at least one wind turbine blade based on a difference in pressurebetween a location of the first pressure sensing orifice and a locationof the second pressure sensing orifice, a rotation speed of the hub, anambient air pressure, an ambient air temperature, and a pitch angle ofthe at least one wind turbine blade.
 11. The wind turbine of claim 10,wherein the determination of the aerodynamic load of the at least onewind turbine bade includes determining a local dynamic pressure at theat least one wind turbine blade based on the rotation speed of the hub,the ambient air pressure, the ambient air temperature, and the pitchangle of the at least one wind turbine blade.
 12. The wind turbine ofclaim 11, wherein the controller is configured to determine the localdynamic pressure by estimating a wind speed and a local air speed at theat least one wind turbine blade.
 13. The wind turbine of claim 12,wherein the controller is configured to determine whether the pitchangle of the at least one wind turbine blade is greater than a minimumpitch angle, and, in response to determining the pitch angle of the atleast one wind turbine blade is not greater than the minimum pitchangle, estimate the wind speed of the at least one wind turbine bladeusing the rotation speed of the hub.
 14. The wind turbine of claim 12,wherein the controller determines whether the pitch angle of the atleast one wind turbine blade is greater than a minimum pitch angle, and,in response to determining the pitch angle of the at least one windturbine blade is greater than the minimum pitch angle, estimate the windspeed of the at least one wind turbine blade using the pitch angle ofthe at least one wind turbine blade.
 15. A method for relating apressure differential to an aerodynamic force at an airfoil, the methodcomprising: determining, by a controller, a local air pressure at anairfoil's surface; determining, by the controller, an ambient airpressure away from the airfoil's surface; determining, by thecontroller, a pressure differential, wherein the pressure differentialis a difference between the local air pressure and the ambient airpressure; determining, by the controller, an aerodynamic forceassociated with the airfoil; and determining, by the controller, arelationship between the aerodynamic force and the pressuredifferential.
 16. The method of claim 15, wherein the determining therelationship between the aerodynamic force and the pressure differentialcomprises: determining a pressure differential coefficient; determiningan aerodynamic force coefficient; and deriving a relationship betweenthe pressure differential coefficient and the aerodynamic forcecoefficient.
 17. The method of claim 16, wherein the deriving therelationship between the pressure differential coefficient and theaerodynamic force coefficient comprises determining a linearrelationship between the pressure differential coefficient and theaerodynamic force coefficient.
 18. The method of claim 16, wherein thederiving the relationship between the pressure differential coefficientand the aerodynamic force coefficient comprises determining a quadraticrelationship between the pressure differential coefficient and theaerodynamic force coefficient.
 19. The method of claim 16, wherein thedetermining the pressure differential coefficient and the determiningthe aerodynamic force coefficient comprises determining a dynamicpressure at the airfoil.
 20. The method of claim 19, wherein thepressure differential coefficient is the difference of the local airpressure and the ambient air pressure divided by the dynamic pressure,and wherein the aerodynamic force coefficient is the aerodynamic forcedivided by the product of the dynamic pressure and the nominal area onwhich the aerodynamic force is acting.